Optimize Costs for Google Kubernetes Engine: Challenge Lab Task 1: Create our cluster and deploy our app Make sure that you:
Create the cluster in the us-central1 region, Use onlineboutique-cluster as the cluster name according to the naming scheme for team-resource, Make the zonal cluster with only two (2) nodes, and Start with machine type n1-standard-2 (2 vCPU, 8G memory).
The following example will create the cluster to the zone us-central1-a using the command-line tools.
Set the zone as a variable in the Cloud Shell.
ZONE=us-central1-a Run the following to create the cluster with the specified configuration:
gcloud container clusters create onlineboutique-cluster
--project=${DEVSHELL_PROJECT_ID} --zone=${ZONE}
--machine-type=n1-standard-2 --num-nodes=2
After the GKE cluster is created, you need to set up the namespaces dev and prod.
kubectl create namespace dev kubectl create namespace prod You will deploy the application to the dev namespace. Switch the current namespace from default to dev:
kubectl config set-context --current --namespace dev Copy the application files to the Shell environment, and then deploy OnlineBoutique app to GKE:
git clone https://github.com/GoogleCloudPlatform/microservices-demo.git cd microservices-demo kubectl apply -f ./release/kubernetes-manifests.yaml --namespace dev Wait until the load balancer exposes an External IP for the frontend-external service. You can monitor the service status using the following command:
kubectl get svc -w --namespace dev Press CTRL+C to stop the monitoring.
Open http://<EXTERNAL_IP> in a new tab. You should see the homepage of the Online Boutique application like this:
Task 2: Migrate to an Optimized Nodepool Make sure that you:
create a new node pool named optimized-pool, configure custom-2-3584 as the machine type, and set the number of nodes to 2; migrate the application to the new node pool by cordoning off and draining default-pool; and delete the default-pool after the migration.
Run the following to create the node pool as specified:
gcloud container node-pools create optimized-pool
--cluster=onlineboutique-cluster
--machine-type=custom-2-3584
--num-nodes=2
--zone=$ZONE
Wait until the status of new node pool becomes OK.
Cordon and drain the default-pool:
for node in $(kubectl get nodes -l cloud.google.com/gke-nodepool=default-pool -o=name); do kubectl cordon "$node"; done
for node in $(kubectl get nodes -l cloud.google.com/gke-nodepool=default-pool -o=name); do kubectl drain --force --ignore-daemonsets --delete-local-data --grace-period=10 "$node"; done Verify if your pods are running on the new, `optimized-pool, node pool:
kubectl get pods -o=wide --namespace dev With the pods migrated, it’s safe to delete the default-pool:
gcloud container node-pools delete default-pool
--cluster onlineboutique-cluster --zone $ZONE
Task 3: Apply a Frontend Update
Set a pod disruption budget for your frontend deployment. Name it onlineboutique-frontend-pdb and set the min-availability of your deployment to 1.
kubectl create poddisruptionbudget onlineboutique-frontend-pdb
--selector app=frontend --min-available 1 --namespace dev
Use kubectl edit to update resources:
KUBE_EDITOR="nano" kubectl edit deployment/frontend --namespace dev Change the following in the configuration:
image to gcr.io/qwiklabs-resources/onlineboutique-frontend:v2.1, and imagePullPolicy to Always Save the file changes.
(Optional) In the Cloud Console, navigate to Kubernetes Engine > Workloads and click the frontend deployment. Go to the REVISION HISTORY tab, you should see the latest revision updates to onlineboutique-frontend:v2.1
Task 4: Autoscale from Estimated Traffic You need to apply horizontal pod autoscaling to your frontend deployment with:
scaling based on a target CPU percentage of 50, and setting the pod scaling between 1 minimum and 13 maximum.
Run the following to configure the autoscaler:
kubectl autoscale deployment frontend --cpu-percent=50
--min=1 --max=13 --namespace dev
Check the status of the autoscalers by running:
kubectl get hpa --namespace dev Update your cluster autoscaler to scale between 1 node minimum and 6 nodes maximum.
gcloud beta container clusters update onlineboutique-cluster
--enable-autoscaling --min-nodes 1 --max-nodes 6 --zone $ZONE
To test the autoscalers, run the following to perform a load test to simulate the traffic surge.
kubectl exec $(kubectl get pod --namespace=dev | grep 'loadgenerator' | cut -f1 -d ' ')
-it --namespace=dev -- bash -c "export USERS=8000; sh ./loadgen.sh"
The command produces traffic on the store from a loadgenerator pod with a high number of concurrent users.
Navigate to the OVERVIEW tab of the frontend deployment, you should see a sharp increase in CPU, Memory, and Disk utilization after the load test started.
Scroll to the Managed Pods section, you should observe the number of pods increases by the horizontal pod autoscaling.
Eventually, you will also see new nodes initiate by the cluster autoscaling. But you need to keep patient for a while.
Congratulations! You completed this challenge lab.